Despite being touted as a significant technology trend, ‘Big Data’ programs have proven to be difficult to implement. How can businesses get it right?
The majority of business executives understand that Big Data has been a serious technology disruptor yet few have achieved success with their initiatives.
The survey found that only a quarter of the businesses surveyed classified their initiatives as successful, be they proof of concept, partially implemented or fully operational.
One could argue that the investment has led to unsuccessful outcomes, but given its potential as a game-changer for the future of business, what are businesses getting wrong and what measures can be put in place to set up Big Data projects for success?
Why are Big Data Projects so Challenging?
According to the study, the key challenges to getting these projects right included:
- Scattered data in silos across different teams
- Absence of a clear business case for funding and implementing Big Data projects
- Ineffective coordination of Big Data and analytics projects teams across the organisation
- Dependency on legacy systems for data processing and management
- Ineffectual governance models for Big Data and Analytics
- A lack of top management sponsorship
- Lack of clarity on Big Data tools and technology requirements
- The cost for tools and infrastructure
- Data security and privacy concerns
- Internal resistance to change within the organisation.
The survey flagged key technology challenges and in various degrees, vendors, technologists and Big Data Specialists have begun to address these challenges. However what this list also reveals is the importance of guiding principles behind successful project delivery, which are:
- Having a clear business case for any project
- Ensuring that there is effective coordination between project teams
- Implementing good governance
- Engaging the right sponsors
- Clarity around which tools should be used
- Bringing the team along on the journey
Defining what success looks like then qualifying it and putting in place the fundamentals of project management is essential for successful project delivery. Without it, the old adage rings true: “Failing to plan means planning to fail” and that’s where many Big Data projects become unstuck, as we explore below.
The Business Case
More than two-thirds of businesses starting on their Big Data journey do not have well-defined criteria with which to measure the success of their initiatives, a critical activity for providing clear project goals and benchmarks for success.
Without a strong business case, starting on a project is like a ship starting off its journey without a destination, map or compass and still expecting to arrive. Ensuring the business case is clear enables the executive and sponsors to understand the investment they signed off has not been wasted and the project has actually achieved something of importance for the business.
Tip: Have a clearly defined business case that identifies the problem, how it will be solved and what the benefit/s will be. Tailor it for the audience, i.e. CFO may be interested in the ROI, whereas the CMO may be more interested in the impact on Marketing.
Effective Coordination and Engagement Between Teams
Big Data projects impact a business across many teams, for example, IT, procurement, marketing, finance, sales and so on. Given that most Big Data initiatives require significant investment, these teams should be engaged throughout the lifecycle of the Big Data project.
Strong executive sponsorship is critical to success to ensure the project follows a top-down approach to drive this collaboration among teams. Without it, a Big Data initiative could result in lots of potentially aimless, unconnected activities being executed within the business under the banner of a Big Data project.
Tip: Appoint a strong sponsor and support them with strategically placed champions (leaders) across the organisation.
Implementing Good Governance
There are three elements that will help deliver success if put in place appropriately: project governance, data governance and data ownership. These are critical because they ensure that the right information is provided to the right people at the right time throughout a project’s delivery.
Tip: Review your data governance structure and identify the opportunities for improvement. Involve stakeholders across the organisations and establish buy in, KPIs and metrics that will ensure success.
Engaging the Right Influencers to Bring Users Along for the Journey
As Big Data projects impact on multiple parts of the organisation, aligning the stakeholders with a unified vision and engendering strong buy-in is critical to success. A short iterative “fail fast” approach delivers proof of concepts and quick wins, which will enable the project to demonstrate tangible value which can then be communicated to the wider business to build credibility and momentum. Clear consistent and tailored messaging, combined with strategic change leadership from the Big Data champions is a formula for success.
Tip: Always be generous in the amount to invest in change and communication management. It is the soft factor that contributes greatly to success. This team provides clarity, can break up the pockets of change resistance and ensures that messaging is strong and consistent.
Get the Fundamentals Right from the Beginning
Big Data is becoming a critical tool for businesses and the ability to build a top-down strategy and successfully deliver to the strategy will provide a significant competitive advantage. Other tips for Big Data projects include:
- Establish a well-defined organisational unit for Big Data initiatives that is closely integrated with business teams, to deliver a local business view of insights
- Create a senior leadership role for Big Data and analytics to signal the shift to a data-driven culture
- Establish clear criteria and metrics to measure the success of initiatives
Using good project delivery practices as outlined above complemented with the right technology will take you a long way towards success with your Big Data projects.
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